PROJECT SUMMARY Following the implementation of the Affordable Care Act (ACA), millions of Americans have gained coverage, many for the first time in their lives. The law has created more options for affordable coverage and put millions into the driver seat when it comes to selecting their coverage and enrolling in a health plan. This dissertation seeks to improve our understanding of consumer decision-making in this new health insurance landscape. Through a comprehensive investigation of consumer behavior during the insurance decision-making process, this dissertation will provide needed updates to the literature on this topic. It will also help policymakers and agencies better evaluate how consumers will respond to policies that change their available coverage options. All three papers in the proposed dissertation will either focus on or include data from California, the most populous and diverse state in the country. California has been a leader in promoting the policies of the ACA and has fully embraced the law by expanding Medicaid and creating its own state-based marketplace. The first paper will explore the transitions Californians and Texans make over time between health insurance types (e.g. between Medicaid and the individual market). While a health insurance transition that leads an individual to gain coverage can improve their access to care, others can lead to lapses in care [12]. Using the Medical Expenditure Panel Survey (MEPS), Kaplan-Meier based models will be employed to estimate monthly transition probabilities for each initial insurance source and to identify the consumer characteristics associated with transitioning coverage types. Separate models will be run for each state and five different MEPS cohorts, covering the three years prior to ACA-implementation and the first three years under the law. The second paper will examine two key components of health plans that individuals weigh when making enrollment decisions ? cost and quality. The ACA requires both federally-facilitated and state-based marketplaces to provide easy to understand plan quality information to customers shopping for coverage. Through analysis of a hypothetical choice experiment and Covered California enrollment data, this paper will seek to understand the tradeoffs consumers make between cost and quality and explore how they respond to changes in a plan's quality rating. This project will use conditional probit and nested conditional logit models to estimate the consumer characteristics associated with a preference for cost or quality. The third paper will look at consumers who switched health plans during open enrollment in California's health insurance marketplace, Covered California. Under the ACA, switching rates in the individual market have been much higher than those previously seen in other markets [16]. Looking at re-enrollees in Covered California, this paper will provide data on consumer switching behavior over time and will employ multiple logistic regression models to identify the consumer, plan, and market-level characteristics associated with consumers' decisions to change their coverage during open enrollment.